Tech Briefs Magazine - October 2021 - MD-22

gence. The machine learning algorithms
were able to distinguish among
all the speeds with each finger with high
accuracy.
The team compared four different
ma chine learning algorithms for their
successful classification capabilities: Knearest
neighbor (KNN), support vector
machine (SVM), random forest (RF),
and neural network (NN). The time-frequency
features of the liquid metal sensors
were extracted to train and test the
machine learning algorithms. The NN
generally performed the best at the
speed and texture detection with a single
finger and had a 99.2 percent accuracy
to distinguish among ten different
multi-textured surfaces using four liquid
metal sensors from four fingers simultaneously.
Although
advances in prosthetic limbs
have been beneficial and allow ampu -
tees to better perform their daily duties,
they do not provide them with sensory
information such as touch. They also
Researchers used individual fingertips fitted with stretchable tactile sensors with liquid metal on a prosthesis
attached to a robotic arm. (Photo by Alex Dolce)
don't enable them to control the prosthetic
limb naturally with their minds.
The new technology could help provide
amputees with a more natural prosthetic
Independent Collaborative Robots
Artificial intelligence helps train robots to work together to move an object around two obstacles
and through a narrow door in computer simulations.
University of Cincinnati, Ohio
If you've ever helped someone
move furniture, you know it
takes coordination - simultaneously
pushing or pulling and
reacting based on what your
helper is doing. Researchers
have developed artificial intelligence
to train robots to work
together to move a couch - or
in this case a long rod that served
as a stand-in - around two obstacles
and through a narrow door
in computer simulations.
much difference since the others
can compensate to complete
the mission.
The robots were given the
task of carrying the virtual
couch around two obstacles and
Robots are being engineered to work independently on tasks that require cooperation.
(Photo: Colleen Kelley/UC Creative + Brand)
The team sought to accomplish the task
with as little communication as possible
between the robots. Neither robot directed
the other and the two robots didn't
share their strategy in advance to complete
the task. Instead, they turned to an
artificial intelligence called genetic fuzzy
logic. Fuzzy logic is an intelligent control
technique that mimics human reasoning
by replacing a simple binary classification
(yes, no) with degrees of right or wrong.
22
Cov
ToC
Genetic algorithms modify individual so -
lutions to " learn " from past results to optimize
performance over time.
Ultimately, the team wants to expand
to 10 or more robots working cooperatively
on a project. To build a habitat in
space, many robots will need to work
together. But if relying on a communications
network and it goes down, the
whole project fails. If robots can work
independently, losing one won't make
through a narrow door. The
robots successfully completed
the task 95% of the time in simulations.
More importantly, the
robot work partners were 93%
successful in a completely new
scenario with two new unfamiliar
obstacles and a target door in a different
location. And the robots had nearly
equal success without re-training, even
when researchers changed other factors
such as the size of the couch.
The control system is scalable, which
means the team can add any number of
robots to a task.
For more information, contact Michael
Miller at michael.miller3@uc.edu; 513-5566757.
Motion
Design, October 2021
device that can " feel " and respond to its
environment.
For more information, contact Gisele
Galoustian at ggaloust@fau.edu.

http://info.hotims.com/79418-936

Tech Briefs Magazine - October 2021

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